Perspectives of ChatGPT in Pharmacology Education, and Research in Health Care: A Narrative Review
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- 1Department of Pharmacology, Government Medical College, Surat, Gujarat, India.
Published in Journal of Pharmacology and Pharmacotherapeutics
Correspondence: Chetna R. Patel
Department of Pharmacology, Government Medical College, Surat, Gujarat, India.
Email: drchetnapatel2012@yahoo.com
Copyright: © 2023 The Author(s). This is an open access article.
Published: Jan 1, 2023, Received: Aug 17, 2023, Accepted: Oct 5, 2023
Abstract
In the era of advanced Open artificial intelligence (AI) technology, the large language model tool known as chat generative pre-training transformer (ChatGPT) is gaining an increasing number of users in various fields such as healthcare, medical education, agriculture, and customer support due to its features like information retrieval, generating humanlike conversations, and natural language processing. The purpose of this narrative review is to present the perspectives of ChatGPT in pharmacology and medical education. And highlight the limitations of ChatGPT in these areas and draw the attention of policymakers in healthcare to implement such technologies while taking into consideration ethical issues. To collect information regarding the perspectives of ChatGPT in Pharmacology and Medical Education. And highlight the limitations of ChatGPT in these areas. In health care, it helps in the drug discovery and development process, diagnosis, treatment, counseling, assisting in surgical procedures, pharmacovigilance, pharmacy, and so on. In medical education, this tool plays a crucial role in online tutoring, personalized assistance, grading, improvement in grammar, and so on. Despite the limitations, ChatGPT is helpful in healthcare, medical education, and scientific writing. To overcome such limitations of ChatGPT, like ethical issues, emotionlessness, providing information before 2021, the risk of biases, uncontrollability, lack of transparency, academic dishonesty, and so on, alternatives have been developed, but they also fail to entirely resolve the associated limitations. Looking at the current scenarios, there is an urgent need for comprehensive guidelines to address these limitations and provide a framework for appropriately utilizing AI tools in healthcare domains. This framework should also focus on maintaining a balance between human involvement and technological advancements.
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